System and method for detecting and tracking features in images
First Claim
1. A method for detecting and tracking a feature in an image, comprising the steps of:
- obtaining a set of training images clustered into clustered shape subspaces representative of at least one non-linear shape manifold in the training images;
receiving an image in which identification of a feature in the image is desired and movement of the feature has occurred with respect to a previous image;
creating an initial shape for identifying the feature in the image;
searching through the clustered shape subspaces to find a potential matching shape which potentially matches the feature;
deforming the initial shape into the potential matching shape; and
continuing searching and deformation until a final shape indicative of the feature is obtained.
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Abstract
A system and method for tracking features, e.g., facial features, is provided, which allows for the tracking of features which move in a series of images and whose shape changes nonlinearly due to perspective projection and complex 3D movements. A training set of images is processed to produce clustered shape subspaces corresponding to the set of images, such that non-linear shape manifolds in the images are represented as piecewise, overlapping linear surfaces that are clustered according to similarities in perspectives. A landmark-based training algorithm (e.g., ASM) is applied to the clustered shape subspaces to train a model of the clustered shape subspaces and to create training data. A subsequent image is processed using the training data to identify features in the target image by creating an initial shape, superimposing the initial shape on the target image, and then iteratively deforming the shape in accordance with the model until a final shape is produced corresponding to a feature in the target image.
30 Citations
20 Claims
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1. A method for detecting and tracking a feature in an image, comprising the steps of:
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obtaining a set of training images clustered into clustered shape subspaces representative of at least one non-linear shape manifold in the training images; receiving an image in which identification of a feature in the image is desired and movement of the feature has occurred with respect to a previous image; creating an initial shape for identifying the feature in the image; searching through the clustered shape subspaces to find a potential matching shape which potentially matches the feature; deforming the initial shape into the potential matching shape; and continuing searching and deformation until a final shape indicative of the feature is obtained. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification